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  1. 1

    LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

    LimiX-2 is a new tabular foundation model that replaces the usual target‑centric in‑context learning objective with a joint‑distribution objective via Contextual Mechanism Networks (CMNs). Trained on synthetic causal graphs using Context‑Conditional Masked Modeling, it outperforms prior tabular PFNs on TabArena, TALENT, and BCCO and can recover causal skeletons from attention patterns.

    Hugging Face Daily Papersarxiv.org2 minpaper
  3. 3

    When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts

    Cloudflare’s Page Shield uses a graph‑neural‑network (GNN) to model JavaScript as a syntax‑tree graph, followed by a lightweight LLM for second‑opinion triage and an ensemble of frontier models for deep analysis. This pipeline caught eight malicious payloads across four distinct affiliate‑theft and backdoor techniques that traditional scanners missed, demonstrating the need for runtime, behavior‑…

    Cloudflarecloudflare.com21 minHN2
  4. 4

    Online Learning with LLM Experts from Limited Feedback

    The paper models prompt routing to multiple LLM experts as a bandit problem with limited feedback and proposes algorithms that achieve sublinear regret in both full‑information and bandit settings. Experiments demonstrate that the methods learn effective routing strategies across diverse LLMs using only a small feedback budget.

    Hugging Face Daily Papersarxiv.org2 minpaper
  5. 5

    Presentation: Complexity and Creativity in Software Engineering

    Phillip Mortimer argues that AI‑generated code makes all software effectively "write‑only" due to volume, and proposes managing this by treating tests as the sole specification, automating code reviews with LLMs, and decoupling intent from implementation.

    InfoQinfoq.com28 mintalk
  6. 6

    Scaling Telco Autonomy: Leveraging GNNs with Distributed GraphFlow

    Google Cloud’s blog introduces Distributed GraphFlow (DGF), an open‑source Python library for building and scaling Graph Neural Networks (GNNs) on a Spanner‑backed digital twin of telecom networks. The post outlines the three‑layer architecture (digital twin on Spanner Graph, ML layer with DGF, AI agents) and highlights DGF’s high‑level API (5‑line example) and low‑level primitives, but provides…

    Google Cloud Bloggoogle.com3 min
  7. 7

    ML based ranking using Nrtsearch

    Yelp added an Inference Plugin to Nrtsearch that runs XGBoost and neural‑network models inside the search engine, eliminating a separate scoring service. The plugin extracts features from index documents, loads MLeap bundles from MLflow, and serves predictions on replica nodes with millisecond latency.

    Yelp Engineeringyelp.com7 min
  8. 8

    What is AIOps?

    Databricks’ blog post explains what AIOps is, its core components (data ingestion, normalization, anomaly detection, correlation, RCA, automation, collaboration), and why it’s gaining traction now. It positions AIOps as a layer between observability and action, emphasizing human‑in‑the‑loop for high‑risk steps, and outlines domain‑centric vs. domain‑agnostic approaches and common use‑cases like R…

    Databricksdatabricks.com13 min
  9. 9

    Data and AI Conferences to Attend in 2026 and 2027

    A curated list of ~70 data, AI, and ML conferences for 2026‑2027, grouped by region and topic. The post explains why keeping an up‑to‑date list matters for budgeting and roadmap visibility, but offers no technical insight beyond event names and dates.

    Moove-itqubika.com3 min